The distinctiveness of brain structures and circuits depends on interacting gene products, yet the organization of these molecules (the "transcriptome") within and across brain areas remains unclear. High-throughput, neuroanatomically-specific gene expression datasets such as the Allen Human Brain Atlas (AHBA) and Allen Mouse Brain Atlas (AMBA) have recently become available, providing unprecedented opportunities to quantify molecular neuroanatomy. This dissertation seeks to clarify how transcriptomic organization relates to conventional neuroanatomy within and across species, and to introduce the use of gene expression data as a bridge between genotype and phenotype in complex behavioral disorders.
The first part of this work examines large-scale, regional transcriptomic organization separately in the mouse and human brain. The use of dimensionality reduction methods and cross-sample correlations both revealed greater similarity between samples drawn from the same brain region. Sample profiles and differentially expressed genes across regions in the human brain also showed consistent anatomical specificity in a second human dataset with distinct sampling properties.
The frequent use of mouse models in clinical research points to the importance of comparing molecular neuroanatomical organization across species. The second part of this dissertation describes three comparative approaches. First, at genome scale, expression profiles within homologous brain regions tended to show higher similarity than those from non-homologous regions, with substantial variability across regions. Second, gene subsets (defined using co-expression relationships or shared annotations), which provide region-specific, cross-species molecular signatures were identified. Finally, brain-wide expression patterns of orthologous genes were compared. Neuron and oligodendrocyte markers were more correlated than expected by chance, while astrocyte markers were less so.
The localization and co-expression of genes reflect functional relationships that may underlie high-level functions. The final part of this dissertation describes a database of genes that have been implicated in speech and language disorders, and identifies brain regions where they are preferentially expressed or co-expressed. Several brain structures with functions relevant to four speech and language disorders showed co-expression of genes associated with these disorders. In particular, genes associated with persistent developmental stuttering showed stronger preferential co-expression in the basal ganglia, a structure of known importance in this disorder.